Evidence map›Paper›PMID 27670136›Full record

ArticleBMC medical research methodology2016

The contribution of databases to the results of systematic reviews: a cross-sectional study.

Lisa Hartling, Robin Featherstone, Megan Nuspl, Kassi Shave, Donna M Dryden, Ben Vandermeer

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 14 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 14 pooled it
6.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 14 syntheses or guidelines pooled it, 116 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Lisa HartlingCochrane Child Health, University of Alberta, ECHA4-472, 11405-87 Avenue, Edmonton, AB, T6G 1C9, Canada. hartling@ualberta.ca.
Robin FeatherstoneAlberta Research Center for Health Evidence (ARCHE), University of Alberta, 11405-87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Megan NusplAlberta Research Center for Health Evidence (ARCHE), University of Alberta, 11405-87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Kassi ShaveAlberta Research Center for Health Evidence (ARCHE), University of Alberta, 11405-87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Donna M DrydenAlberta Research Center for Health Evidence (ARCHE), University of Alberta, 11405-87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Ben VandermeerAlberta Research Center for Health Evidence (ARCHE), University of Alberta, 11405-87 Avenue, Edmonton, AB, T6G 1C9, Canada.
University of Alberta · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOne of the best sources for high quality information about healthcare interventions is a systematic review. A well-conducted systematic review includes a comprehensive literature search. There is limited empiric evidence to guide the extent of searching, in particular the number of electronic databases that should be searched. We conducted a cross-sectional quantitative analysis to examine the potential impact of selective database searching on results of meta-analyses.

methodsOur sample included systematic reviews (SRs) with at least one meta-analysis from three Cochrane Review Groups: Acute Respiratory Infections (ARI), Infectious Diseases (ID), Developmental Psychosocial and Learning Problems (DPLP) (n = 129). Outcomes included: 1) proportion of relevant studies indexed in each of 10 databases; and 2) changes in results and statistical significance of primary meta-analysis for studies identified in Medline only and in Medline plus each of the other databases.

resultsDue to variation across topics, we present results by group (ARI n = 57, ID n = 38, DPLP n = 34). For ARI, identification of relevant studies was highest for Medline (85 %) and Embase (80 %). Restricting meta-analyses to trials that appeared in Medline + Embase yielded fewest changes in statistical significance: 53/55 meta-analyses showed no change. Point estimates changed in 12 cases; in 7 the change was less than 20 %. For ID, yield was highest for Medline (92 %), Embase (81 %), and BIOSIS (67 %). Restricting meta-analyses to trials that appeared in Medline + BIOSIS yielded fewest changes with 1 meta-analysis changing in statistical significance. Point estimates changed in 8 of 31 meta-analyses; change less than 20 % in all cases. For DPLP, identification of relevant studies was highest for Medline (75 %) and Embase (62 %). Restricting meta-analyses to trials that appeared in Medline + PsycINFO resulted in only one change in significance. Point estimates changed for 13 of 33 meta-analyses; less than 20 % in 9 cases.

conclusionsMajority of relevant studies can be found within a limited number of databases. Results of meta-analyses based on the majority of studies did not differ in most cases. There were very few cases of changes in statistical significance. Effect estimates changed in a minority of meta-analyses but in most the change was small. Results did not change in a systematic manner (i.e., regularly over- or underestimating treatment effects), suggesting that selective searching may not introduce bias in terms of effect estimates.

Indexed as

BiasKnowledge synthesisLiterature searchingMeta-analysisSystematic reviews

Identifiers

PMID27670136
PMCPMC5037618
OpenAlexW2524295027

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.